Image evaluation method and microscope

ABSTRACT

Image evaluation method capable of objectively evaluating the image resolution of a microscope image. An image resolution method is characterized in that resolution in partial regions of an image is obtained over an entire area of the image or a portion of the image, averaging is performed over the entire area of the image or the portion of the image, and the averaged value is established as the resolution evaluation value of the entire area of the image or the portion of the image. This method eliminates the subjective impressions of the evaluator from evaluation of microscope image resolution, so image resolution evaluation values of high accuracy and good repeatability can be obtained.

BACKGROUND OF THE INVENTION

[0001] The present invention relates to methods for evaluatingmicroscope images such as from scanning electron microscopes andscanning ion microscopes and relates in particular to a method forevaluating image resolution and a microscope having an evaluationfunction.

[0002] In charged particle microscopes such as scanning electronmicroscopes (SEM) and scanning ion microscopes (SIM), the relatedtechniques for evaluating image resolution are roughly divided into twomethods. One is the gap method disclosed in JP-A-45265/1993 forevaluating image resolution by viewing a microscope image of goldparticles deposited by evaporation onto a carbon substrate as a specimenand then finding the minimum visually discernible gap separating theparticles at two points as seen on the monitor display of themicroscope.

[0003] The other is the FFT method as disclosed in JP-A-24640/1999 forevaluating image resolution by frequency analysis of observation imagedata that was subjected to two-dimensional Fourier transform (FFT).

SUMMARY OF THE INVENTION

[0004] The first gap method of the related art has the problem that highaccuracy and repeatability of image resolution evaluation values cannotbe expected because the size and shape of the gold particles to beimaged are not uniform and because the human evaluator may not beobjective when visually determining the minimum gap between twoparticles. The second FFT method of the related art also has the problemthat resolution is visually evaluated with a resolution determinationcurve plotted on a power spectrum graph for frequency analysis, sosubjectivity on the part of the evaluator still cannot be eliminated.

[0005] In the semiconductor manufacturing process in particular,multiple microscopes are used for long periods during the work processfor quality control of semiconductor devices. But image resolution isstill evaluated by the methods of the related art, so the differential(instrumental error) in image resolution between microscopes and changesin resolution over time cannot be accurately controlled, causingproblems making it impossible to minimize variations in device qualityin the device manufacturing process.

[0006] The present invention has the object of providing an imageevaluation method for objectively determining image resolution ofmicroscope images, and a microscope having a resolution evaluationfunction.

[0007] To achieve the above objects, the present invention provides animage evaluation method for evaluating image resolution, wherein theresolution in partial regions of the image is obtained over an entirearea or a portion of the image, averaging is performed over an entirearea or a portion of the image, and the averaged value becomes theresolution evaluation value for an entire area or a portion of theimage. Other objects and examples of the present invention are describedin the detailed description of the preferred embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

[0008]FIG. 1 is a schematic diagram of a scanning electron microscope;

[0009]FIGS. 2A and 2B show microscope images of a gold-evaporatedspecimen used for resolution evaluation;

[0010]FIGS. 3A and 3B show the noise elimination effects of the imageprocessing method of the present invention on SEM images;

[0011]FIG. 4 shows an SEM image of a dimensional calibration specimen(pitch dimension: 0.240±0.001 μm);

[0012]FIG. 5 shows changes over time in image resolution over one month,displayed on the monitor display of SEM equipment A and B;

[0013]FIGS. 6A and 6B illustrate an evaluation example of astigmaticimages using azimuth resolution;

[0014]FIG. 7 shows an example of an inspection device evaluation system;

[0015]FIG. 8 is a schematic diagram showing local image resolution;

[0016]FIG. 9 is a flow chart for calculating image resolution.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0017] Preferred embodiments of the present invention are next describedin detail based on the following drawings. The outline of a scanningelectron microscope (called SEM hereafter) is explained below as apreferred embodiment of the present invention. The electron lens systemin FIG. 1 focuses a charged particle beam (electron beam) 2 emitted froma charged particle source (electron gun) 1 onto a specimen 4 by anelectron lens 3 and scans the beam over the specimen 4 in any desiredsequence. Secondary particles (secondary electrons) 5 generated from thesurface of the specimen 4 by irradiation of the electron beam aredetected by a secondary particle detector system 6. The output of thedetector system 6 is input as image data to a control system 7 (controlprocessor) having an image processing and control function. The specimen4 can be moved along in any direction in the three dimensions by use ofan X-Y-Z stage 8. The control system 7 also controls the chargedparticle source (electron gun) 1, the electron lens 3, the secondaryparticle detector system 6, X-Y-Z stage 8, and an image display device9.

[0018] In this embodiment, the electron beam 2 is two-dimensionallyscanned over the surface of the specimen 4 with a scanning coil (notshown in drawing). The signal detected with a secondary electrondetector in the secondary particle detector system 6 is transferred toan image memory after being amplified by a signal amplifier in thecontrol system 7 and is finally displayed as an image of the specimen onthe image display device 9. The secondary signal detector may be asecondary electron or reflected electron detector, photodetector orX-ray detector.

[0019] The address signals corresponding to the memory positions in theimage memory are generated in the control system 7 or a separatelyinstalled computer, and supplied to a scanning coil after beingconverted into analog signals. When for example, the image memory has512×512 pixels, the X-direction address signal is a digital signalrepresenting 0 to 512 repeatedly. The Y-direction address signal is alsoa digital signal representing 0 to 512 repeatedly but is incremented by1 each time the X-direction address signal reaches 512 from 0. Thesedigital signals are converted into analog signals.

[0020] Since the addresses in the image memory correspond to addressesof deflection signals for scanning the electron beam, a two-dimensionalimage in the electron beam deflection range determined by the scanningcoil is stored in the image memory. The signals in the image memory canbe sequentially read out in time series by a readout address generatorcircuit synchronized with a readout clock. The signals that were readout according to each address are converted into an analog signal andinput to the image display device 9 as a brightness-modulated signal.

[0021] The image memory has a function for storing images (image data)while superimposing (synthesizing) them in order to improve thesignal-to-noise ratio. For example, one complete image is created bystoring images obtained with 8 two-dimensional scans while superimposingthem. In other words, a final image is created by synthesizing imagesthat were formed by one or more X-Y scans. The number of images (frameintegration count) for creating one complete image can be setarbitrarily to an optimum value in view of factors such as theefficiency of generating secondary electrons. Another final image canalso be created as needed by further superimposing images that werecreated by integrating multiple image frames. When or after the desirednumber of images has been stored, blanking may be performed with theprimary electron beam to stop the input of information to the imagememory.

[0022] When the frame integration count is set to 8, a sequence may bemade so that the first image frame is deleted when the ninth image frameis input so that there are always 8 image frames. Weighted averaging canalso be performed, for example, by adding the product of the imageintegrated in the image memory times (×) ⅞, to the ninth image when theninth image is input.

[0023] The control system 7 has an input device (not shown in drawing)that specifies the image acquisition conditions (scanning speed, numberof images to be integrated), field-of-view correction method and howimages should be output or saved. In addition, the control system 7incorporates a memory medium (not shown in drawing) for storing varioustypes of data.

[0024] This embodiment of the present invention also provides a functionthat forms a line profile based on the detected secondary electrons orreflected electrons. Such a line profile should be formed based on thequantity of detected electrons when a specimen is scannedone-dimensionally or two-dimensionally with the primary electron beam,or based on the brightness information of the specimen image. A lineprofile obtained this way will be used, for example, to measure thedimensions of patterns formed on a semiconductor wafer.

[0025] The schematic diagram in FIG. 1 was explained with the controlsystem 7 as an in integral or semi-integral unit of the scanningelectron microscope. However, the embodiment of the present invention isnot limited by this example and may have an external control processorinstalled separately from the scanning electron microscope to performthe processing explained below. This case will require transfer mediafor sending the signals detected with the secondary signal detector tothe control processor or sending the signals from the control processorto the electron lens and deflector of the scanning electron microscope,and also an input/output terminal for inputting and outputting thesignals sent by way of the transfer media.

[0026] Furthermore, this embodiment of the present invention alsoprovides a function that for example, allows storing the observationconditions (measurement points, optical conditions for electron scanningmicroscope, etc.) in advance as a guide to help assist in viewingmultiple points on a semiconductor wafer. Measurement and observationcan easily be performed according to the contents of this guide.

[0027] A program intended to perform the processing explained below maybe stored in the memory medium and executed with a control processorhaving an image memory and supplying signals necessary for the scanningelectron microscope. In other words, the following embodiment of thepresent invention may be established as a program invention used forcharged-particle beam equipment such as scanning electron microscopeswith an image processor. A specimen is placed on stage 8 of thisembodiment for evaluating image resolution as explained below.

[0028] Particles of gold having a large atomic number are typicallydeposited by evaporation on a carbon substrate and used as a specimenfor evaluating image resolution. FIGS. 2A and 2B show SEM images oftypical gold particle specimens. These are digital images consisting of512×512 pixels. Image resolution is calculated by the evaluationalgorithm explained below. The concept for evaluating image resolutionis shown in FIG. 8 along with the gap resolution evaluation method, andthe flow chart for calculating image resolution is shown in FIG. 9. Adetailed description is given in the following embodiments.

[0029] First Embodiment

[0030] In the present embodiment, a microscope image is treated as animage of a three-dimensional object viewed from one direction, and thegradient and curvature of the object surface at each pixel point P arefirst obtained. Next, the hypothetical shortest distance required forthe object to be distinguished from the surrounding area, or in otherwords, the local resolution is calculated from the gradient and theminimum contrast needed to recognize the object. The weighted harmonicmean of the local resolution is then calculated over the entire image,and the mean value is viewed as a typical resolution of the image. Aspecific example for calculating image resolution is explained belowusing the flow chart shown in FIG. 9.

[0031] A microscope image is treated as an image of a three-dimensionalobject viewed in one direction and the geometrical features such as thegradient and radius of curvature of the object shape are calculated byrange image analysis. The image is a digital image consisting of n×npixels. The position of a pixel at an arbitrary point on the image isconsidered as (x, y), and the density at the pixel as “z”. To calculatethe gradient and radius of curvature of the object shape at point P(x,y), a local region (partial region) comprised of m×m pixels (normally,m=5) with the center at point P is clipped out and the shape of thelocal surface is approximated by multi-degree equation z(x, y). Here, aquadratic equation is used as a multi-degree equation for approximatingwith a curved surface, as expressed in the quadratic equation (Eq. 1)below.

z(x, y)=ax ² +by ² +cxy+dx+ey+f   (Eq. 1)

[0032] To obtain a fitting or matching with the curved surface, thecoefficients “a” to “f” are determined so that the sum-square value ofthe fitting error is minimal. Once these coefficients are determined,the gradient g(x, y; θ) [θis azimuth angle of gradient] of the localsurface can be found by the following geometrical calculation (Eq. 2).

g(x, y; θ)={(δz/δx)²+(δz/δy)²}^(½)  (Eq. 2a)

θ=arctan{(δz/δy)/(δz/δx)}  (Eq. 2b)

[0033] The radius of curvature, Rc, can also be similarly computed.Applying this approximated curved surface is also effective ineliminating the noise of the image. More specifically, by clipping out apart of an image containing noise and approximating it with a curvedsurface or plane, the noise can be partially eliminated, allowingcalculation of the gradient with fewer adverse effects from noise.

[0034] In view of the noise elimination effect and reduction incalculation time, a local region of a 5×5 pixel size (m=5) is preferableand a quadratic equation is suitable for this size. When a local regionof a 3×3 pixel size (m=3) is used, the calculation time becomes shorter,but the effect achieved from eliminating the frequency component noise,especially noise exceeding a period of 3 pixels on the image patternwill be poor compared to cases using the quadratic equation of m=5. Onthe other hand, the 3×3 pixel size was used as the local region size forimages having less noise and containing a large quantity of frequencycomponents having a period of less than 5 pixels on the image patternbecause the gradient calculation accuracy is better. When applying aplane (display functional equation is linear) as the approximate surfaceinstead of the curved surface, the calculation time becomes shorter butthe noise elimination effect is poor compared to cases using the curvedsurface for the quadratic equation display.

[0035] Here, an azimuth angle representing the range from a specificazimuth angle θ_(i)−π/n to θ₁+π/n is expressed as θ₁(i=1, 2, . . . , n;n=36), and the resolution obtained by finding a harmonic mean in theimage while weighting with the weight Wp of the local image resolutionRp having the azimuth angle, is viewed as the azimuth image resolutionR(θ₁). The image resolution R over the entire image is obtained byfinding the geometric mean of this azimuth image resolution R(θ_(i)) byusing the whole azimuth angle. The image resolution calculated this wayis not greatly affected even, for example, if unexpected noise intrudesinto a portion of the microscope image.

1/R(θ_(i))=[∫{Wp(x, y)/Rp(x, y;θ_(i))}dxdy]/[∫Wp(x, y)dxdy]  (Eq. 3a)

Rp(x, y; θ ₁)=2ΔC/|g(x, y; θ _(i))|  (Eq. 3 b)

R={R(θ₁), R(θ₂), . . . , R(θ_(n))}^(1/n)   (Eq. 4)

[0036] Here, ΔC is the threshold contrast needed to discern a gap on theobject shape that corresponds to the resolution, and is proportional tothe maximum amplitude of the expected density value E{z} calculated fromEq. 1. When the proportional coefficient is considered as Kc, ΔC isgiven as follows (normally, Kc=0.1).

ΔC=Kc·[E{z(max)}−E{z(min)}]  (Eq. 5)

[0037] The local weight Wp can be considered as the gradient g only (Eq.6a) or the product (Eq. 6b) of g times [E{z(x, y)}−E{z(min)}]. Thelatter is used when evaluating an image in which the gradient, g, islarge and more attention should be paid to bright portions. This greatlyrelieves the effects of brightness on the resolution when brightness ischanged.

Wp(x, y)=|g(x, y)|  (Eq. 6a)

[E{z(x, y)}−E{z(min)}]·|g(x, y)|]  (Eq. 6b)

[0038] Here, one way to calculate the local resolution with highaccuracy when the applied surface is a curved surface is by calculatingthe Wp (Eq. 6) limited to cases where assuming that ½ of that value(=Rp/2) is less than the absolute value of the minimum radius of thecurvature, and setting Wp=0 in all other cases. The standard deviation σof density (corresponding to image noise) which is a parameter forevaluating image quality can also be calculated by using the local noiseσ_(p).

σ={1/(n−2)}{Σ(σ_(p) ²)}^(½)(m=5)   (Eq. 7a)

σ_(p)={1/m}{Σ[z(x, y)−E{z(x, y)})]²}^(½)  (Eq. 7b)

[0039] The embodiment of the present resolution evaluation method isexplained using FIGS. 2A and 2B. Shown in FIG. 2A and FIG. 2B are images(512×512 pixels) of a specimen prepared for resolution evaluation,photographed with an SEM under different optical conditions. Imageresolution Rcg by the present evaluation method and image resolutionRgap by the gap method of the related art are shown by the resolutionratio between the conditions A and B, along with evaluation errorscaused by multiple human evaluators.

[0040] In either resolution, the R(b)/R(a) ratio is larger than 1, butthe gap method of the related art shows an error due to multipleevaluators, which is as large as ±50%. However, the error occurring inthe present evaluation method is 0 as long as the same image data isused.

[0041] The resolution evaluation algorithm stated above determines allparameters required for calculation by using only the informationpossessed by the image. The present evaluation method uses an algorithmthat is not vulnerable to subjective impressions of human evaluators andhas the following advantages:

[0042] (1) Subjectivity of the evaluator accompanying the conventionalgap method of resolution evaluation can be eliminated, so images can beobjectively evaluated.

[0043] (2) Calculation is performed on real space so that calculationparameters are easy to understand as a physical quantity. (Calculationis performed on frequency space by the FFT method.)

[0044] (3) Not only resolution but also the standard deviation ofdensity (image noise) can be calculated and evaluated.

[0045] (4) Signal-to-noise ratio, image quality, viewing magnificationaccuracy (or error) can be calculated and evaluated.

[0046] (5) Not susceptible to changes in brightness and image noise.

[0047] (6) Applicable to specimens with a high directional pattern (Notpossible with the FFT method). Not susceptible to effects occurring fromcontamination on the specimen.

[0048] (7) Resolution can be evaluated among multiple microscopes basedon the same specimen (image), allowing the instrumental error(differential between microscopes) to be easily found.

[0049] In particular, advantage (1) allows objective comparison of imageresolution between microscopes of the same type and is very helpful tothe users when selecting the microscope model. The present embodimentwas explained as an example for obtaining image resolution over theentire specimen image, but preferred embodiments are not limited to it.Resolution in a specific region of the specimen image (smaller than theentire image but larger than a local region used for calculating thelocal resolution Rp) may also be calculated. For instance, an imageregion selecting device (pointing device, etc.) not shown in the drawingmay be connected to the control system 7 to select any desired size atany position on the image, so that image resolution in a regioncorresponding to the selected image is computed. This method eliminatesbackground information not directly relating to the measurement objectand acquires actual image resolution in the region to be measured. Inaddition, the throughput for calculating image resolution can beimproved since the calculation is performed only on a specific region.

[0050] Second Embodiment

[0051] As the second embodiment, a scanning electron microscope (SEM)utilizing the present image evaluation method is explained below. Thescanning electron microscope is just one example, so the present imageevaluation method can be applied to most inspection devices in whichimages must be accurately evaluated.

[0052] On a semiconductor device production line, as shown in FIG. 7,multiple SEMs 701 to 704 are connected by a network to the mastercomputer 705 for measuring and controlling the length of semiconductordevice patterns.

[0053] Each SEM has an image resolution computing function based on theabove image resolution evaluation method, which is installed in thecomputer of the SEM control system. Self-evaluation of image resolutioncan be implemented by an instruction from the equipment operator. Theresolution evaluation value appears on the monitor that also displaysthe microscope image.

[0054] On the SEMs that have been used to measure and control the lengthof device patterns for extended periods of time, image resolution ofeach SEM is periodically evaluated by using the specimen for imageresolution evaluation, displayed and recorded, along with theinformation on changes in the evaluation value. These periodicallyevaluated resolution values are stored in the master computer 705 wherethe data is collectively managed together with the information fromother SEMs. If an image resolution evaluation value falls outside theallowable range or value, the operator is informed of the error on thatmicroscope and master computer. The master computer 705 has an imagedisplay monitor and an image processor as explained earlier. The displaymonitor shows that the image resolution evaluation value is outside theallowable range or value. As specific display formats, information onchanges in evaluation values on multiple SEMs may be graphicallyrepresented while distinguishing the allowable range from the areaoutside it. In another possible format, illustrations of multiple SEMmodels may be displayed on the monitor as shown in FIG. 7 and theillustration of the model on the display may start flashing if itsevaluation value falls outside the allowable range or value. Using thesedisplay formats prevents the measurement accuracy from deterioratingeven if a measurement error occurs due to a differential occurringbetween microscopes (instrumental error). In this embodiment, if theoutput image from an inspection device indicates a resolution evaluationvalue outside the allowable range, the error is displayed or stored inmemory so that the instrumental error between each inspection device canbe controlled while maintaining high resolution.

[0055] On the microscope where the error occurred, a command foradjusting the optical system which is one inspection parameter is issuedby an instruction from the operator or from the program installed in thecontrol system. The lens system is then controlled by the signal basedon the evaluation value through the control system of the microscope, sothat the image resolution is set within the specified allowable range.Information on the adjustment process is stored in the SEM that causedthe error and also sent to the master computer. In this example, eachSEM evaluated its own image resolution; however the master computer forsystem control may evaluate the resolution of images sent from each SEMand send the evaluation value signal back to each SEM. Based on thisevaluation value signal, each SEM controls the lens system through thecontrol system of the microscope in the same way as described above inorder to set the image resolution within the specified allowable range.

[0056] In this way, differences in resolution occurring among multipleSEMs can be simultaneously measured and controlled. If an error isfound, the above method is used to make an adjustment. This reducesdifferences in device quality between each production process andmaintains uniform quality. Uniform quality in device production can alsobe maintained in the same way among factories in different locations bycommunicating this information.

[0057] Third Embodiment

[0058] An embodiment is next described in detail using the previouslydescribed image resolution evaluation specimen. In this embodiment, adimensional calibration specimen (JP-A-31363/1996) was used as an imageresolution evaluation specimen having an absolute dimensional pattern.FIG. 4 shows an SEM image of this calibration specimen. The pitchdimension of the grid pattern formed on a silicon substrate is anextremely accurate 0.240±0.001 μm.

[0059] Using this specimen allows highly accurate magnificationcalibration of SEM images. This means that pixels used as size units formicroscope digital images can now be converted into or converted fromactual dimensional units (for example, nanometers) with high accuracy,allowing the resolution evaluation value R in the present invention tobe displayed in length units (for example, nanometers). However, becausethe pattern of the specimen used here consists of vertical lines, theimage resolution is not calculated from the average in all azimuthdirections, but instead uses the image resolution in an azimuthdirection (horizontal direction in the case of FIG. 4) showing a minimumvalue among azimuth image resolution values calculated from Eq. 3a.

[0060] The resolution evaluation value R is convenient during actual usebecause it is displayed in units of actual dimensions (length) that donot depend on the viewing magnification. In pixel unit display on theother hand, a specified number of pixels is allocated to the imageresolution value, making it convenient to directly calculate the optimumviewing magnification. In an image resolution display, length units areusually used, but the pixel unit or both units can also besimultaneously displayed at the discretion of the equipment operator. Bypresetting the number of pixels to be allocated for image resolution,the viewing magnification can be automatically set for variousspecimens.

[0061] Image resolution and signal-to-noise ratio (SNR) are parametersused for evaluating image quality of a microscope images. When theaverage of the expected density value E{z} is Zav, the signal S can beapproximated as S=Zav−E{z(min)}, and the noise N can be approximated asN=σ. (See Eq. 7.), the SNR can then be obtained as follows.

SNR=[Zav−E{z(min)}]/σ  (Eq. 8)

[0062] If the fine structure pattern is the focus of the image qualityparameter, and C is utilized as the maximum amount of information (bitunits) per pixel in that structure pattern, then C can be calculatedfrom the following equation using the image resolution value R of pixelunits.

C={log₂(1+SNR)}/R ²   (Eq. 9)

[0063] The image can therefore now be evaluated in terms of imageresolution, noise, and image quality. By setting a threshold level forat least one of these evaluation parameters to determine whether theimage is a pass (acceptable) or a fail (reject), the image that wasobtained can be judged as acceptable or a reject based on thesepass/fail parameters as well as each evaluation value.

[0064] The image display device displays different messages according tothe evaluation value and pass/fail results (for example, whether thethreshold level is exceeded, to what extent the threshold level wasexceeded, etc.). The messages to be displayed can also be selected bythe equipment operator. The messages may be stored in the controlprocessor memory for readout later on.

[0065] Fourth Embodiment

[0066] The viewing magnification accuracy (or error) is discussed next.The image resolution evaluation value (unit: μm) of a microscope imagetaken with a dimensional calibration specimen under a particular viewingmagnification is considered as R, the absolute pitch dimension of thedimensional calibration specimen as L, and the error as Δ× (units: μm).The dimensional calibration specimen has dimensions of L=0.240 μm andΔ×=0.001 μm in this example. On the surface of this specimen, arepetitive pattern having a square-wave cross section is fabricated bysilicon anisotropic etching. Each square-wave edge sharply risesperpendicular to the specimen surface.

[0067] After correcting the image rotation so that the grid patternimage of the dimensional calibration specimen is vertical on the displaymonitor, the viewing magnification is calibrated while measuring thepitch dimension at multiple points (about 10 to 20 points) at amagnification of 5 to 100,000, so that the average is 0.240 μm. In otherwords, the scan area of the electron beam is changed so that themeasured average value approaches 0.240 μm. The pitch dimensions of thepattern itself have an error of a few nanometers so the measurementsmade at these multiple points are averaged to reduce the error. At thispoint, the magnification error E and magnification accuracy P on thepercentage (%) display are calculated as follows.

E=100×{(Δ×)² +R ²}^(½) /L   (Eq. 10)

P=100−E   (Eq. 11)

[0068] Verification using general scanning electron microscopesconfirmed that respective viewing magnification errors E within ±2% and±0.5% were obtained. These results prove that, like image resolution,the viewing magnification accuracy and error can be controlled with highaccuracy versus microscope differentials (instrumental error) andchanges over time not only for an individual microscope but also formultiple microscopes.

[0069] Changes in data over elapsed time on these evaluation parameterscan also be displayed as needed on the image display device in a graphicor spreadsheet format by an instruction from the equipment operator.FIG. 5 shows typical graphical changes in the image resolution over onemonth, displayed on the image display monitor of SEM equipment A and B.The figure clearly shows that image resolutions on both units ofequipment are held within the range between 3.2 and 3.8. If theresolution deviates from this range, the equipment should be serviced.This graph also proves that due to an instrument error the resolution ofequipment B is 0.1 better than equipment A, even though the imageresolutions of both pieces of equipment are within the allowable range.Based on this instrument error, a coefficient for correcting theinstrumental error between the two units of equipment is found and usedto correct the measurement length value. As a result, semiconductordevice production can now be controlled while the instrument errorbetween the microscopes is minimized.

[0070]FIGS. 6A and 6B show an example of evaluation of astigmatic imagesusing azimuth resolution. FIG. 6A shows microscope images of goldparticles with correction parameter s. p. values at 0, 40 and 80 hourson the astigmatic image control system installed in the microscopecontrol system 7. Azimuth image resolutions at this point are plotted ona polar coordinate in FIG. 6B. The azimuth image resolution curve isnearly circular at s.p.=0, but increases at azimuths of 17 and 35(direction of arrow) as the s.p. value increases to 40 and then 80,while exhibiting little change at azimuths of 8 and 26 (direction ofarrow). These changes indicate the extent of image blur in FIG. 6A. Thisimage blur corresponds to the beam spread in the microscope. (See theimage at s.p.=80 in FIG. 6A.) A microscope capable of automaticallyperforming focus adjustment and astigmatic correction with high accuracycan be achieved by installing in the computer in the control system 7, aprogram combining the azimuth image resolution evaluation method withthe optimization method to minimize evaluation values in all azimuthdirections.

[0071] The above embodiment was explained using SEM, but similar effectswere attained from a scanning transmission electron microscope (STEM)and scanning ion microscope (SIM). In the STEM, the specimens are thinfilms and the brightness signals used for image construction aresecondary electrons, primary electrons transmitting through thespecimen, or X-rays emitted by excitation of primary electrons. In thecase of SIM, since spattering damage occurs on the specimen surface fromion beams which are not used by the SEM or STEM, the same point on thespecimen cannot be observed at high magnification. Therefore, becausethe present evaluation method is “applicable to specimens with a highdirectional pattern” mentioned as the advantage (5) earlier, a widerrange of specimens can now be used for resolution evaluation. Thepresent evaluation method has proven very effective in improving theoperability and the accuracy of image resolution during actual use.

[0072] The above embodiments were explained using microscopes as thedevice of the embodiment. However, the image resolution evaluationmethod of the present invention can also be used in equipment utilizingmicroscope images for beam positioning and setting the beam irradiationarea, for example of charged-particle beam systems such as focused ionbeam machining systems, electron beam diagnostic equipment, electronbeam exposure systems. Therefore, the “microscopes” mentioned hereinclude “charged-particle beam systems” utilizing microscope images.

[0073] The present invention uses a technique by which a microscopeimage is treated as an image of a three-dimensional object viewed fromone direction and is approximated to a curved surface (or plane)described with a multi-order (or linear) function z=f(x, y) for eachlocal region. This technique is also very effective as an imageprocessing method for reducing image noise. The density distributionafter image processing is definitely the E {z(x, y)} distribution of Eq.7. FIGS. 3A and 3B show the image processing effects on SEM images of aresolution standard specimen. FIG. 3A is the original image and FIG. 3Bis the processed image. The image of FIG. 3B appears smooth because ofthe noise elimination effect.

[0074] The present invention can be applied not only to SEM and SIM butalso to any microscope using the gap method and FFT method of therelated art as the image resolution evaluation method, for example,optical microscopes, and scanning probe microscopes. Likewise, the imageprocessing method of the present invention has the effect of eliminatingnoise on all microscope images as well as SEM and SIM.

[0075] The microscope image resolution evaluation process of the presentinvention is further not susceptible to the subjective impressions ofthe evaluators, so image resolution evaluation values can be obtainedwith high reliability and repeatability.

[0076] In the image resolution evaluation method using a magnificationcalibration specimen, optical characteristics are precisely adjusted bymaking use of the evaluation value signal so that the desired imageresolution, magnification, image noise and image quality can bemaintained and controlled with a high degree of accuracy.

[0077] Furthermore, when the present invention is applied to multiplemicroscopes used for quality control in semiconductor device production,the differential (instrumental error) in image resolution between eachmicroscope and changes in resolution over time can be accuratelycontrolled, making it possible to minimize variations or irregularitiesin device quality during the device manufacturing process.

What is claimed is:
 1. An image evaluation method for evaluating theresolution of an image, comprising the steps of: obtaining theresolution in partial regions of the image over the entire area of theimage or a portion of the image; performing averaging over the entirearea of the image or a portion of the image; and establishing theaveraged value as the resolution evaluation value of the entire area ora portion of the image.
 2. An image evaluation method according to claim1, wherein the resolution in partial region is obtained from the densitygradient in each of the partial regions and weighted averaging isperformed over the entire area or portion of the image.
 3. An imageevaluation method according to claim 2, wherein with the density of theimage as z, and a position in an arbitrary partial region within theimage as (x, y), the curved surface or plane of a multi-order or oneorder function z=f(x, y) is applied to each of the partial regions, andthe gradient of the density is obtained from the differential value ofthe function.
 4. An image evaluation method for evaluating theresolution of an image, comprising the steps of: obtaining the gradientin a portion of an image; calculating the distance needed to recognizethe portion from the gradient; performing the calculation over theentire area of the image or portion of the image; and establishing asthe resolution evaluation value, the result obtained by averaging thevalues obtained from the calculations over the entire area of the imageor portion of the image.
 5. An image evaluation method for evaluating animage, comprising the steps of: calculating the image resolution andimage noise evaluation values; calculating the image evaluationparameters based on the image resolution and image noise evaluationvalues that were calculated; and evaluating the image using the imageevaluation parameters.
 6. An image evaluation method according to claim5, wherein the image evaluation parameters are the maximum amount ofinformation that can be possessed per one pixel in the structuralpattern on an image.
 7. An inspection device evaluation system connectedto multiple inspection devices via a network for evaluating the imagesacquired with these inspection devices, wherein images acquired with themultiple inspection devices are evaluated, and if any of the evaluationvalues falls outside the allowable range or setting value specified forthe evaluation values of the images acquired with the multipleinspection devices, a result is displayed or a command is issued toadjust the inspection conditions of the inspection device whose valueswere outside the allowable range or setting value.
 8. A charged-particlebeam microscope comprising: a charged particle source; a detector thatdetects secondary particles released from a specimen when irradiatedwith a charged particle beam emitted from the charged particle source;and a control processor that constructs an image based on the output ofthe detector, wherein the control processor obtains the resolution ofpartial regions of the image over the entire area of the image orportion of the image, performs averaging over the entire area of theimage or portion of the image, and calculates the image resolution valueof the entire area or portion of the image.
 9. A charged-particle beammicroscope according to claim 8, wherein the control processorcalculates the resolution of partial regions based on the densitygradient in the partial regions of the image.
 10. A charged-particlebeam microscope according to claim 8, wherein the control processorperiodically calculates the resolution evaluation value and displays orstores the calculated resolution evaluation value along with informationon changes over time.
 11. A charged-particle beam microscope accordingto claim 8, wherein along with the resolution, the control processorcalculates the image noise of the image, signal-to-noise ratio of theimage or at least one of the image evaluation parameters calculatedbased on the resolution.
 12. A charged-particle beam microscopeaccording to claim 11, wherein the control processor has a function forsetting threshold values for the resolution evaluation value, the imagenoise, the signal-to-noise ratio of the image or at least one of theimage evaluation parameters, and if the resolution, the image noise, thesignal-to-noise ratio of the image or the image evaluation parameterexceed the threshold level, the result is shown on the display device orstored in memory.
 13. A charged-particle beam microscope according toclaim 11, wherein the control processor periodically evaluates theresolution evaluation value, the image noise, the signal-to-noise ratioof the image or at least one of the image evaluation parameters, anddisplays or stores the evaluation value along with information onchanges over time.
 14. A charged-particle beam microscope according toclaim 8, wherein the control processor displays the magnificationaccuracy or magnification error on the display device.
 15. Acharged-particle beam microscope according to claim 8, wherein theresolution evaluation value is in units of length.
 16. Acharged-particle beam microscope according to claim 8, wherein thecontrol processor finds the local resolution from the density gradientin each of the partial regions and performs weighted averaging over theentire area or a portion of the image.
 17. A charged-particle beammicroscope according to claim 16, wherein with density of the image as zand a position in an arbitrary partial region within the image as (x,y), the control processor applies the curved surface or plane of amulti-order or linear function z=f(x, y) to each of the partial regions,and finds the density gradient from the differential value of thefunction.
 18. An image processing method, wherein with density of theimage as z and a position in an arbitrary partial region of the image as(x, y), the curved surface or plane expressed in a multi-order or linearfunction z=f(x, y) is applied as an approximation to each of the partialregions.
 19. A charged-particle beam microscope comprising: a chargedparticle source; a detector that detects secondary particles releasedfrom a specimen when irradiated with a charged particle beam emittedfrom the charged particle source; and a control processor thatconstructs an image based on output of the detector, wherein the controlprocessor applies a curved surface or plane as an approximation to apartial region of the image, this processing is performed over theentire image or a portion of the image, and the results are synthesizedto construct an image.
 20. An image construction method for constructingan image based on the charged particles released from the scanned regionon a specimen when scanned by a charged particle beam emitted from acharged particle source, wherein multiple patterns having the samedimensions on the specimen are scanned by the charged particle beam tomeasure the length of the patterns, and the scan area of the chargedparticle beam is changed so that the average of the measurement lengthresults approaches the dimensions of the patterns.